Graduate
Institute of Graduate Studies
Geomatics (without thesis)
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Data Processing & Analysis

Course CodeSemester Course Name LE/RC/LA Course Type Language of Instruction ECTS
İMSY 1108 1 Data Processing & Analysis 3/0/0 CC English 9
Course Goals
To help students understand fundamentals of errors, error propagation, probability, least square adjustment, statistical tests, filters and best fitting lines and surfaces.
Prerequisite(s) None
Corequisite(s) None
Special Requisite(s) None
Instructor(s) Professor Kamil EREN
Course Assistant(s) None
Schedule Will be announced at the beginning of semester
Office Hour(s) Will be announced at the beginning of semester
Teaching Methods and Techniques -Lecture,discussion
Principle Sources -MORITZ H., Physical Geodesy, 2005
Other Sources -SMITH S.O., Datum, Ellipsoids, Grids, and Grid Reference Systems, The Defense Mapping Agency, 1996 SMITH S.O., The Universal Grids: UTM and UPS, The Defense Mapping Agency, 1989De BOOR C., Spline Toolbox for Use with MATLAB, 2003GAUSS C.F., Abhandlungen zur Methode der Kleinsten Quatrate, Berlin 1889
Course Schedules
Week Contents Learning Methods
1. Week Measurement errors, Sources of errors, Precision and accuracy, tolerans values Oral presentation
2. Week General laws of probability Oral presentation
3. Week Error distribution models and error analysis Oral presentation
4. Week Accuracy tests and criterions Oral presentation
5. Week Adjustment methods Oral presentation
6. Week Conditioned measurements adjustment Oral presentation
7. Week Correlated measurements adjustment Oral presentation
8. Week Network adjustment Oral presentation
9. Week Other adjustment methods Oral presentation
10. Week Filtering; Kalman filtering Oral presentation
11. Week Approximation methods and models Oral presentation
12. Week Best fitting lines Oral presentation
13. Week Best fitting surfaces Oral presentation
14. Week Practices Oral presentation
15. Week
16. Week
17. Week
Assessments
Evaluation tools Quantity Weight(%)
Midterm(s) 1 25
Homework / Term Projects / Presentations 1 25
Final Exam 1 50


Program Outcomes
PO-1Develop and deepen knowledge in the field of Geomatics Engineering.
PO-2Conceive the interdisciplinary interaction which the field of Geomatics Engineering is related with.
PO-3Use of theoretical and practical knowledge within the field of Geomatics Engineering at a proficiency level.
PO-4Interpret the knowledge about the field of Geomatics Engineering by integrating the information gathered from different disciplines and formulate new knowledge.
PO-5Solve the problem faced related to the field of Geomatics Engineering by using research methods.
PO-6Independently conduct studies that require proficiency in the field of Geomatics Engineering
PO-7Take responsibility and develop new strategic solutions as a team member in order to solve unexpected complex problems faced within the applications in the field of Geomatics Engineering.
PO-8Demonstrate leadership in contexts that require solving problems related to the field of Geomatics Engineering.
PO-9Evaluate knowledge and skills acquired at proficiency level in the field of Geomatics Engineering with a critical approach and direct the learning.
PO-10Communicate current developments and studies within the field of Geomatics Engineering to both professional and non-professional groups systematically using written, oral and visual techniques by supporting with quantitative and qualitative data.
PO-11Investigate, improve social connections and their conducting norms with a critical view and act to change them when necessary.
PO-12Communicate with peers by using a foreign language at least at a level of European Language Portfolio B2 General Level.
PO-13Use advanced informatics and communication technology skills with software knowledge required by the field of Geomatics Engineering.
PO-14Audit the data gathering, interpretation, implementation and announcement stages by taking into consideration the cultural, scientific, and ethical values and teach these values.
PO-15Develop strategy, policy and implementation plans on the issues related to the field and assess the findings within the frame of quality processes.
PO-16Use the knowledge, problem solving and/or implementation skills in interdisciplinary studies.
Learning Outcomes
LO-11.To learn measurement errors
LO-22.To learn probability,
LO-33.To learn adjustment methods,
LO-44.To learn statistical tests,
LO-55.To learn filters,
LO-66.To learn best fitting lines and surfaces.
Course Assessment Matrix:
Program Outcomes - Learning Outcomes Matrix
 PO 1PO 2PO 3PO 4PO 5PO 6PO 7PO 8PO 9PO 10PO 11PO 12PO 13PO 14PO 15PO 16
LO 1
LO 2
LO 3
LO 4
LO 5
LO 6